Title: On-board monitoring of air path for automotive IC engines

Authors: Adnan Hamad; Dong-Ya Zhao; Ding-Li Yu; Quan-Min Zhu

Addresses: Control Systems Research Group, School of Engineering, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK ' Department of Chemical Industrial Equipment, and Control Engineering, College of Chemical Engineering, China University of Petroleum, Qingdao, 266580, China ' Control Systems Research Group, School of Engineering, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK ' Bristol Institute of Technology, University of the West of England, Frenchay Campus, Coldharbour Lane, Bristol, BS16 1QY, UK

Abstract: Fault detection and isolation have become one of the most important aspects of automobile design. A new fault detection and isolation (FDI) scheme is developed for automotive engines in this paper. The method uses a radial basis function (RBF) neural network to model engine dynamics, and the modelling errors are used to form the basis for residual calculation. Furthermore, another RBF network is used as a fault classifier to isolate different faults from the modelling errors. The method is developed and the performance assessed using the engine benchmark, the mean value engine model (MVEM) with MATLAB/Simulink. Five faults have been simulated on the MVEM, including three sensor faults, one component fault and one actuator fault. The three sensor faults considered are 10%-20% change superimposed on the outputs of manifold pressure, temperature and crankshaft speed sensors; one component fault considered is air leakage in intake manifold and exhaust gas recycle (EGR); the actuator fault considered is the malfunction of fuel injector. The simulation results showed that all the simulated faults can be clearly detected and isolated in the dynamic condition throughout the operating range.

Keywords: automotive engines; neural networks; fault detection; fault isolation; vehicle design; on-board monitoring; air path; modelling; engine dynamics; simulation; sensor faults; component faults; actuator faults; manifold pressure; temperature; crankshaft speed; air leakage; intake manifold; exhaust gas recirculation; EGR; fuel injection.

DOI: 10.1504/IJMIC.2013.055908

International Journal of Modelling, Identification and Control, 2013 Vol.20 No.1, pp.1 - 15

Published online: 27 Sep 2014 *

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